Sökning: "ADMM"

Visar resultat 1 - 5 av 20 avhandlingar innehållade ordet ADMM.

  1. 1. Optimization and Learning for Large-Scale MIMO-OFDM Wireless Systems : Theory, Algorithms, and Applications

    Författare :Shashi Kant; Carlo Fischione; Mats Bengtsson; Bo Göransson; Gabor Fodor; Christoph Studer; KTH; []
    Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; First-Order Optimization; Convex Optimization; ADMM; Three-operator ADMM TOP-ADMM ; EVM; OOBE; PAPR; ACLR; MIMO; OFDM; Federated Learning; Telecommunication; Telekommunikation; Optimeringslära och systemteori; Optimization and Systems Theory; Electrical Engineering; Elektro- och systemteknik;

    Sammanfattning : The requirements for next-generation wireless communications networks, particularly fifth-generation (5G) and beyond, are driven by at least three broad use cases. These include enhanced mobile broadband services to support extremely high data rates in terms of network or per user in both uplink and downlink, massive machine-type communications to accommodate massive internet-of-things applications, and critical machine-type communications to handle mission-critical applications that require ultra-high reliability and low latency. LÄS MER

  3. 2. Study on Decentralized Machine Learning and Applications to Wireless Caching Networks

    Författare :Yu Ye; Ming Xiao; Zhu Han; KTH; []
    Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Distributed multi-task learning; decentralized optimization; ADMM; mobility-aware wireless caching; Distribuerat lärande med flera uppgifter; decentraliserad optimering; ADMM; mobilitetsmedveten trådlös cache; Electrical Engineering; Elektro- och systemteknik;

    Sammanfattning : To promote the development of distributed machine learning, it is crucial to provide efficient models and training algorithms. This thesis is devoted to the design of distributed multi-task learning and decentralized algorithms, as well as the application of distributed machine learning in wireless caching networks. LÄS MER

  4. 3. Accelerating Convergence of Large-scale Optimization Algorithms

    Författare :Euhanna Ghadimi; Mikael Johansson; Angelia Nedich; KTH; []
    Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Convex optimization; Large-scale systems; First-order methods; Convergence analysis; ADMM; Optimization algorithms; Electrical Engineering; Elektro- och systemteknik; Matematik; Mathematics;

    Sammanfattning : Several recent engineering applications in multi-agent systems, communication networks, and machine learning deal with decision problems that can be formulated as optimization problems. For many of these problems, new constraints limit the usefulness of traditional optimization algorithms. LÄS MER

  5. 4. Optimization of low-cost integration of wind and solar power in multi-node electricity systems: Mathematical modelling and dual solution approaches

    Författare :Caroline Granfeldt; Chalmers tekniska högskola; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; variable renewable electricity; Lagrangian relaxation; ADMM; electricity system modelling; variable splitting; capacity expansion; cost optimization; variation management; consensus algorithm; subgradient algorithm;

    Sammanfattning : The global production of electricity contributes significantly to the release of CO2 emissions. Therefore, a transformation of the electricity system is of vital importance in order to restrict global warming. LÄS MER

  7. 5. Group-Sparse Regression : With Applications in Spectral Analysis and Audio Signal Processing

    Författare :Ted Kronvall; Statistical Signal Processing Group; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; sparse regression; group-sparsity; statistical modeling; regularization; hyperparameter-selection; spectral analysis; audio signal processing; classification; localization; multi-pitch estimation; chroma; convex optimization; ADMM; cyclic coordinate descent; proximal gradient;

    Sammanfattning : This doctorate thesis focuses on sparse regression, a statistical modeling tool for selecting valuable predictors in underdetermined linear models. By imposing different constraints on the structure of the variable vector in the regression problem, one obtains estimates which have sparse supports, i.e. LÄS MER